Mathematics Pre-sessional Bootcamp
To accompany the support offered to the under-represented groups that the AI and Data Science Masters Scholarship will benefit, the University of Birmingham is proud to be offering a Mathematics pre-sessional bootcamp for all Home and International students intending to study on one of the nine courses applicable for the scholarship.
The free pre-sessional will enhance the accessibility of our courses by providing an opportunity to learn and enhance the necessary mathematical skills for success in postgraduate study, especially for non-STEM students who may have less experience of data handling and mathematics.
You do not need to be eligible for the AI and Data Science Scholarship to apply for this pre-sessional; applications are welcomed from all Home and International students who intend to study one of the courses featured below.
The pre-sessional bootcamp is intended to support students' confidence in their mathematical comprehension and competency; the bootcamp is not an alternative means of meeting the mathematical requirements for admission onto MSc Data Science or MSc Financial Technology. Similarly, enrolment onto the mathematics pre-sessional bootcamp does not include direct progression onto the MSc degree: you will need to submit a study application via the online admissions portal for your intended Masters course.
How you will learn
The bootcamp will be delivered online to allow you to join from the place that is most convenient to you; travel to Birmingham is entirely optional for students enrolling onto the bootcamp. The bootcamp has been designed to be a self-guided course that provides students with a wealth of resources, such as lecture videos and guided tutorials to problem-solve mathematical tasks. There will be access to an online learning platform to structure your learning as well as access to academics to guide and help with the mathematical tasks. You can access help from the academic supervisors online as well as having the option to arrange in-person sessions to further consolidate your learning.
The bootcamp will be taking place online between Tuesday 27 August and Friday 20 September 2024. Due to the course's design of being self-guided with complimentary academic-led sessions, you are able to study flexibly during the four weeks.
In each week, there will be five sessions that last two hours each; these typically take place between 3.00pm until 5.00pm but may be subject to change depending on academics' teaching schedule. Independent study is advised outside of these times to build your confidence in the mathematical skills, and to best prepare you for these sessions, particularly so that you can identify areas where you would like further assistance from the academic supervisors.
How to apply
This pre-sessional course was available to all Home and International students applying to one of the nine eligible courses above. Applications are now closed. Students who enrolled before the deadline would have received further communication via email before the bootcamp's start date.
What you will learn
Our four-week bootcamp covers foundational topics in mathematics. Some of these topics will be considered as assumed knowledge for the data science portion of the MSc programmes. These topics are central to understanding the underlying principles of data science and machine learning.
- Introduction to Mathematical Notation
- Calculus and Rates of Change
- Probability
- Vectors and Linear Algebra
Teaching and assessment
As an online bootcamp, there will be a two-hour guided study session each day of the bootcamp. Each session will have an associated canvas page which will contain lecture videos, notes and exercises.
After guided study sessions there will also be a Zoom office hour which students are able to drop into for one-to-one support.
Exercise sheets are available alongside pre-recorded lectures. Students are encouraged to discuss exercises with the relevant module lead or peers on the course.
At the end of each topic students are expected to complete a one-hour take-home test and submit this online via Canvas. The test will cover material learnt within the topic. After each test, you will receive a score and personalised feedback.